Cells are soft, viscoelastic materials whose main structural components are proteins and membranes and whose mechanical phenotype can be significantly altered during pathological transformations. For example, during neoplastic progression, cytoskeletal reorganization results in a measurable decrease in the cell's mechanical modulus (Suresh (2007) Acta Biomaterialia, 3: 413-438; Cross, et al. (2007) Nat. Nanotechnol., 2: 780-783), more commonly known as stiffness. Drug treatment can also result in an altered cellular mechanical phenotype: human leukemia cells treated with certain chemotherapy drugs exhibit an increased modulus (Lam, et al. (2007) Blood, 109: 3505-3508). Preliminary results from our laboratory also show that we can detect mechanical transformations of ovarian cancer cells after treatment with microRNA that reverts the cancerous phenotype towards a healthy phenotype, as evaluated by conventional proliferation and apoptosis assays; treated cells are less deformable than base ovarian cancer cells by a statistically significant margin. Thus, a promising fresh perspective for evaluating cancer treatment is to exploit the mechanical signature of cells.
Yet to fully exploit mechanical profiling of cells (e.g., for cancer or other applications) is believed desirable to quantitatively measuring large number of cells (e.g., >102, or >103, or >104, or >105 cells within a day) for statistically significant analysis of cell subpopulations. It is believed this generally requires processing a large number of cells with a throughput that no previous methodology can offer. Current methods for mechanical phenotyping, such as Atomic Force Microscopy (AFM), provide detailed and accurate cell modulus measurements of a small subset of an entire cell population. However, due to slow detection speeds, sample size is typically limited to less than 100 cells/day using current systems that provide quantitative data (see, e.g., FIG. 1). By contrast, a common and powerful technique for cell characterization, Fluorescence Activated Cell Sorting (FACS), operates at detection rates on the order of 104 cells per second and provides population statistics for levels of specific proteins that are assessed by fluorescent markers.